1. Field of the Invention
Embodiments of the invention generally relate to data-processing. More particularly, the invention relates to searching for information on a computer network.
2. Background of the Related Art
Computer networks were developed to allow multiple computers to communicate with each other. In general, a network can include a combination of hardware and software that cooperate to facilitate the desired communications. One example of a computer network is the Internet, a sophisticated worldwide network of computer system resources.
The growing size of networks, particularly the Internet, makes it difficult to locate relevant information in an expedient fashion. As a result, search tools were developed to locate information on the network based on a query input by a user. Two common search methods include the use of search engines and directories, both having capability to search listings. One difference between search engines and directories is in the manner in which each tool compiles listings. Search engines comprise a search tool referred to as a spider, a crawler, or a robot, which builds indexes containing the traversed addresses according to well-known protocols and algorithms. The results are then displayed to the user for review and selection.
A user-input query in the form of search words phrases, keywords, network addresses, etc., prompts the search engine to sift through the plurality of network addresses (typically on the order of millions) in the index to find matches to the user query. Regardless of the particular search tool structure, conventional search tools reside on a server accessible to multiple users. Search queries are sent from the users to the search tools via a network connection. The search tools then parse the query and execute a search algorithm to identify any network addresses containing information matching the query. In theory, spiders are capable of traversing the entire Internet to locate matching URLs. In practice, however, only a small fraction of the Internet is traversed. Directories are similarly limited because the indexes are selectively compiled by human operators.
One problem with conventional search tools is the relevancy of the search results is dependent on the user's ability to craft a query. While searching a network of computers such as the Internet, a user may come across thousands of different network addresses having different themes relating to their query depending on the search engine's method of processing the query, and performing the search. Unfortunately, the results of the search query may not match the user's desired result due to different word meanings, e.g., dialects, slang meanings, and the like. For example, consider the case where a user enters a query about a soft drink by entering a keyword “pop”, which is the user's slang word for soda pop. The search engine may return the results with regard to “pop music”. The user then must modify the query by adding, replacing, and combining the search words, phrases, and the like. Eventually, given the proper query, the search engine may return the proper results to the user. Thus, the search can be frustrating for the user, as they may have to modify the query many times to produce meaningful results.
Therefore, there is a need for a search tool adapted to search network addresses for a user query and provide meaningful and relevant results.